Known in the art are detection systems for detecting an object in a physical environment, and in some cases, detecting a movement thereof. Conventional detection or tracking systems usually use a camera for capturing images and process the images in order to obtain data related to the object. Such data processing of images requires complex algorithms and presents a number of limitations and challenges. For example, such systems are highly sensitive to color, texture, etc. of the object being tracked. Moreover, movements of a person may result in a changing appearance due to light reflection and shading, and associating parts of an object having different colors may present additional challenges. Furthermore, the presence of visible substances such as gases, fog, smoke, confetti, snow, etc. is known to interfere with the image capture. The same applies in low-light environments.
Moreover, conventional tracking systems are generally low-precision tracking systems, namely used for security purposes and generally directed to detection of motion and/or mere presence. As such, systems known in the art are namely detection systems rather than tracking systems. Furthermore, conventional tracking systems are also limited in the amount of data to be processed. Indeed and for example, a camera-based system processes the same amount of data, usually a high number of pixels, irrespective of the number or size of objects to be detected. Moreover, typical camera based systems require positioning the camera at a certain distance with respect to the objects to be detected and the desired area to be detected. Also, the distance of the camera with respect to the objects may interfere with the focus level of the image being captured.
Furthermore, typical applications for tracking or detection systems are usually not critically dependent on time, that is, the time of processing may be relatively long or slightly delayed with respect to the moving object or person being tracked or detected, without incidence on the desired result. Indeed and for example, with a conventional security system, the output may be provided a few seconds after the corresponding movement or presence of the physical object. Moreover, conventional tracking or detection systems are not configured to keep track of undetected objects 38 being hidden either behind another object or which are out of range with respect to the detection field.
Known to the Applicant are U.S. Pat. No. 4,847,688 (NISHIMURA et al.); U.S. Pat. No. 5,414,474 (KAMADA et al.); and U.S. Pat. No. 6,081,619 (HASHIMOTO).
NISHIMURA et al. is directed to a “moving body recognition circuit having a function in which a moving body is correctly recognized by having the body automatically separating from the background” and in which “undesired small movements are excluded”. NISHIMURA et al. disclose a system using a TV camera, the system being provided with a contour-signal generator and a moving body extractor.
HASHIMOTO is directed to a movement pattern-recognizing apparatus having a sensor for detecting a mobile body and for providing binary movement signals indicating the position of the mobile body. The signal changes as time elapses, thus producing movement patterns being stored and compared for recognition by the apparatus. The system of HASHIMOTO uses a substantially fixed sensor providing data on a substantially narrow span. Moreover, the system of HASHIMOTO detects relatively large-scale displacements of a moving object or person.
KAMADA et al. is directed to an apparatus which recognizes a shape and movement of a moving body based on position data of feature points in an image of the moving body, taken by a TV camera. The moving body recognition apparatus includes a feature point position normalization unit for providing normalized coordinates of a feature point. Typically, two image-input units, such as a camera, are required to identify coordinates of each of the feature points using triangulation. Broadly described, KAMADA et al. aim at providing a moving body recognition apparatus capable of recognizing a rotating body by using a single image input unit.
Hence, in light of the aforementioned, there is a need for an improved system which, by virtue of its design and components, would be able to overcome some of the above-discussed prior art concerns.